Results 81 to 90 of about 2,291,078 (312)
The power of microRNA regulation—insights into immunity and metabolism
FEBS Letters, EarlyView.MicroRNAs are emerging as crucial regulators at the intersection of metabolism and immunity. This review examines how miRNAs coordinate glucose and lipid metabolism while simultaneously modulating T‐cell development and immune responses. Moreover, it highlights how cutting‐edge artificial intelligence applications can identify miRNA biomarkers ...
Stefania Oliveto +2 more
wiley +1 more source
Active Learning for Dialogue Act Classification [PDF]
, 2011 Active learning techniques were employed for classification of dialogue acts over two dialogue corpora, the English human-human Switchboard corpus and the Spanish human-machine Dihana corpus.
Gambäck, Björn +2 more
core +1 more source
OBOE: Collaborative Filtering for AutoML Model Selection
, 2019 Algorithm selection and hyperparameter tuning remain two of the most challenging tasks in machine learning. Automated machine learning (AutoML) seeks to automate these tasks to enable widespread use of machine learning by non-experts.
Akimoto, Yuji +3 more
core +1 more source
Active Machine Learning to Test Autonomous Driving
2021 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW), 2021 Abstract—Autonomous driving represents a significant chal- lenge to all software quality assurance techniques, including testing. Generative machine learning (ML) techniques including active ML have considerable potential to generate high quality synthetic test data that can complement and improve on existing techniques such as hardware-in-the-loop and
openaire +3 more sources
Human Gait Activity Recognition Machine Learning Methods
Sensors, 2023 Human gait activity recognition is an emerging field of motion analysis that can be applied in various application domains. One of the most attractive applications includes monitoring of gait disorder patients, tracking their disease progression and the modification/evaluation of drugs.
Jan Slemenšek +6 more
openaire +4 more sources
Systematic Reviews, 2023 Background Conducting a systematic review demands a significant amount of effort in screening titles and abstracts. To accelerate this process, various tools that utilize active learning have been proposed. These tools allow the reviewer to interact with
Gerbrich Ferdinands +7 more
semanticscholar +1 more source
miRNA‐29 regulates epidermal and mesenchymal functions in skin repair
FEBS Letters, EarlyView.miRNA‐29 inhibits cell‐to‐cell and cell‐to‐matrix adhesion by silencing mRNA targets. Adhesion is controlled by complex interactions between many types of molecules coded by mRNAs. This is crucial for keeping together the layers of the skin and for regenerating the skin after wounding.
Lalitha Thiagarajan +10 more
wiley +1 more source
Prediction and optimization of epoxy adhesive strength from a small dataset through active learning
Science and Technology of Advanced Materials, 2019 Machine learning is emerging as a powerful tool for the discovery of novel high-performance functional materials. However, experimental datasets in the polymer-science field are typically limited and they are expensive to build. Their size (< 100 samples)
Sirawit Pruksawan +4 more
doaj +1 more source
DeepAL: Deep Active Learning in Python [PDF]
arXiv, 2021 We present DeepAL, a Python library that implements several common strategies for active learning, with a particular emphasis on deep active learning. DeepAL provides a simple and unified framework based on PyTorch that allows users to easily load custom datasets, build custom data handlers, and design custom strategies without much modification of ...
arxiv
Exposing the limitations of molecular machine learning with activity cliffs.
Journal of Chemical Information and Modeling, 2022 Machine learning has become a crucial tool in drug discovery and chemistry at large, e.g., to predict molecular properties, such as bioactivity, with high accuracy. However, activity cliffs – pairs of molecules that are highly similar in their structure but exhibit large differences in potency – have been underinvestigated for their effect on model ...
Derek van Tilborg +2 more
openaire +2 more sources